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Record W2035179202 · doi:10.1504/ijogct.2014.057799

A new method estimates TEG purity versus reconcentrator temperature at different levels of pressure in gas dehydration systems

2013· article· en· W2035179202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Oil Gas and Coal Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsReboilerTriethylene glycolThermodynamicsDehydrationEthylene glycolChemistryProcess engineeringMaterials scienceChromatographyOrganic chemistryPhysicsDistillationEngineering

Abstract

fetched live from OpenAlex

There are several processes and principles for obtaining high triethylene glycol (TEG) purity in gas dehydration process. All methods are based on the principle of reducing the effective partial pressure of water in the vapour space of the glycol reboiler, and hence obtaining a higher glycol concentration at the same temperature. One of the most common methods for enhancement of the glycol concentration has been by means of pressure reduction in the reboiler. In this article a simple method is developed to estimate TEG purity as a function of reconcentrator (reboiler) temperature and pressure. The results are found to be in excellent agreement with reported data in the literature with average absolute deviation being around 0.05%. The tool developed in this study can be of immense practical value for engineers to have a quick check on TEG purity as a function of reconcentrator (reboiler) temperature and pressure at various conditions without opting for any experimental trials. In particular, engineers would find the approach to be user-friendly with transparent calculations involving no complex expressions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.260
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it